sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
aa2e709180173020503e973912da0a8ba17a283c7501bcd4525496a11031913d | Python | 14,100 | 318 | """
Author: Mingjian He <mh1@stanford.edu>
"""
from .helper_functions import (
np, plt,
initialize_allosc, plot_mtm, plot_innovations,
plot_residual, plot_acf, plot_pacf,
get_innovations, get_knee, get_ar_psd,
fit_ar, plot_fit_line, ebic_calc
)
import pandas as pd
from ..utils import estimate_r... |
1eb9a680151117ffe05ffe7282f14ef0be1cdb695ea3445daad397f367fbdf35 | Python | 14,101 | 230 | #### Master Script 05a: Extract relevance layer values from trained dynAPM models ####
#
# Shubhayu Bhattacharyay
# University of Cambridge
# email address: sb2406@cam.ac.uk
#
### Contents:
# I. Initialisation
# II. Find all top-performing model checkpoint files for relevance layer extraction
# III. Iteratively extract... |
aa02fb7f662b7acb19f7f4e5944bb3e075e48f3a01bd41b7d64424b971e348b9 | Python | 14,117 | 335 | import TCDF
import argparse
import torch
import pandas as pd
import numpy as np
import networkx as nx
import pylab
import copy
import matplotlib.pyplot as plt
import os
import sys
# os.chdir(os.path.dirname(sys.argv[0])) #uncomment this line to run in VSCode
def check_positive(value):
"""Checks if ... |
7e75855ca49482df9994c690684e54fa1599ac2541957cf7eda65a457caac45b | Python | 14,121 | 438 | #!/usr/bin/env python3
"""
These functions search the environment for software dependencies and configuration.
"""
import os
import sys
import subprocess
import logging
import pkg_resources
import re
import glob
import ciftify.utils as util
def find_workbench():
"""
Returns path of the workbench bin/ folder,... |
a70aff7d2fabbeb74518e699610919e9b88f08a5db8fb7be43c6b4264472803e | Python | 14,143 | 288 | from . GenomeTrack import GenomeTrack
import numpy as np
from .. utilities import plot_coverage, InputError, transform, change_chrom_names
import pyBigWig
DEFAULT_BIGWIG_COLOR = '#33a02c'
class BigWigTrack(GenomeTrack):
SUPPORTED_ENDINGS = ['.bw', '.bigwig']
TRACK_TYPE = 'bigwig'
OPTIONS_TXT = GenomeTrac... |
283042e13d73525a02b64924231d1fb223f509ab10295dfab5cb6c8474223a78 | Python | 14,150 | 417 | from itertools import product
from dipy.core.gradients import gradient_table
from dipy.reconst.csdeconv import ConstrainedSphericalDeconvModel
from dipy.reconst.shm import SphHarmFit
from os.path import join, dirname
from tempfile import mkdtemp
from xml.etree import ElementTree as eTree
import imageio
import pygifs... |
c803be404553d4aa012d325ebbd04277e45d40b4c4525ec6113781504db624c5 | Python | 14,158 | 393 | """Shared public and internal value objects."""
from __future__ import annotations
from collections.abc import Iterator, Mapping, Sequence
from dataclasses import dataclass
from datetime import datetime
from os import PathLike
from pathlib import Path
from typing import Any, Literal, TypeAlias, TypeVar, cast
import ... |
543ff993095228f3c9950ae4196fd5a80d610401175dcadeef89aec6dc1aff1b | Python | 14,159 | 295 | # Standard library imports
import os
import datetime as dt
# Data handling and numerical computations
import numpy as np
import pandas as pd
from scipy.stats import pearsonr
from scipy import interpolate
def smooth(df, n=7):
smoothed = pd.DataFrame(index = df.index[n:],
columns = df.... |
6c5882647f302f2deee899ff2f2f68ad533f73103a52f8c0a4b3fc8480d95047 | Python | 14,169 | 364 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any... |
d2829bafb8f293411edd00f452114d8bd7b033bb64f5999e1b71261fc04a0b04 | Python | 14,180 | 333 | import tempfile
import unittest
import cellprofiler_core.preferences
class TestPreferences(unittest.TestCase):
def test_01_01_folder_translations(self):
for expected, value in (
(
cellprofiler_core.preferences.ABSOLUTE_FOLDER_NAME,
cellprofiler_core.preferences... |
d3570743c29a1efb82c871fdcef4c81b2f933d60cc6edb77905f2fd79973a830 | Python | 14,205 | 410 | """
Ported to pytorch thanks to [tstandley](https://github.com/tstandley/Xception-PyTorch)
@author: tstandley
Adapted by cadene
Creates an Xception Model as defined in (Francois Chollet):
* `Xception: Deep Learning with Depthwise Separable Convolutions` - https://arxiv.org/abs/1610.02357
This weights ported from the... |
a25c9c063fc96219d71e9e558c16732f9b6167d18e4d28ab34a6e8eb84b8c29c | Python | 14,223 | 373 | """
Implementation of Proof-of-Concept Network: StarNet.
Papers:
* `Rewrite the Stars` - https://arxiv.org/abs/2403.19967
We make StarNet as simple as possible [to show the key contribution of element-wise multiplication]:
- like NO layer-scale in network design,
- and NO EMA during training,
- which woul... |
bcfacfa9fb67382a6a172cd02ab996b8134d7d6ae663da755a2a461e6a7ca54a | Python | 14,239 | 355 | import sys
import types
import numpy as np
import pytest
import torch
from PIL import Image
from timm.data import create_dataset, create_loader, create_naflex_loader, create_reader, create_transform
from timm.data.loader import MultiEpochsDataLoader
from timm.data.naflex_loader import NaFlexPrefetchLoader
from timm.d... |
ba6ad3f1214fa3b0b7af38eef9be8137461a28c1b7fa44dd41aea0e9e64e83e7 | Python | 14,241 | 347 | """Prepare BRCA1 regression data directly from the official TCGA Level 3 archive."""
from __future__ import annotations
import argparse
import csv
import gzip
import hashlib
import json
import re
import shutil
import subprocess
import sys
import tarfile
import tempfile
import zlib
from datetime import UTC, datetime
f... |
9c8693224a0b963388b33339821d58bfc49393f190d04ad009bbbcbdbcb7b8a5 | Python | 14,248 | 382 | """Prepare the original Gisette values and splits from UCI without scaling."""
from __future__ import annotations
import argparse
import csv
import gzip
import hashlib
import io
import json
import platform
import shutil
import subprocess
import sys
import zlib
from collections import Counter
from datetime import UTC,... |
b7a10748d25fbad030d1768c5b86083ef7a83594f3e7e9117e01aa3c904edc64 | Python | 14,256 | 445 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
MIT License
Copyright (c) 2022 Pawan Goyal
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation th... |
32609db0263daeb238e1ebfcff0d4c93aba9797361b49bce5ab8c9c3de4746fe | Python | 14,269 | 493 | #!/usr/bin/env python3
import os
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from baycomp import two_on_single
from etspredict.prediction.scoring_utils import compare_propabilites
####################################################################... |
71333eb0c42ffb48039f85c06a15ff7bf1baf9a5d60386ddfcd7ba8b964862a8 | Python | 14,277 | 407 | from rdkit import Chem
import json
from rdkit.Chem import AllChem,Draw,Descriptors
import copy
import pandas as pd
import re
import matplotlib.pyplot as plt
import lib.Reaction_Library as RL
### Reduction Functions:
def G1_function(metab_smiles):
reactant = Chem.MolFromSmiles(metab_smiles)
prod_list = []
... |
a20a4213ff33afd98b071dc9dfe696fb06a1e2ba0fc7241009ec4528861fa16c | Python | 14,282 | 408 | from rdkit import Chem
import json
from rdkit.Chem import AllChem,Draw,Descriptors
import copy
import pandas as pd
import re
import matplotlib.pyplot as plt
import lib.Reaction_Library as RL
### Reduction Functions:
def G1_function(metab_smiles):
reactant = Chem.MolFromSmiles(metab_smiles)
prod_list = []
... |
1e582a239ede44622e6f9ff85e411d416829421a3ad8ed1f6bb71a3bdc62c379 | Python | 14,283 | 354 | """Patch-level random erasing augmentation for NaFlex Vision Transformers.
This module implements random erasing specifically designed for patchified images,
operating at the patch granularity rather than pixel level. It supports two modes:
- 'patch': Randomly erases individual patches (speckle-like noise)
- 'region':... |
9a556ac9553b38cb6d324c9957d5c48daa4461dee8fa79c4780ae96e7dd60883 | Python | 14,291 | 379 | import uuid
# import tensorflow.compat.v2 as tf
import tensorflow as tf
from keras import activations
from keras import backend
from keras import constraints
from keras import initializers
from keras import regularizers
from keras.engine import base_layer
from keras.engine.input_spec import InputSpec
from keras.layers... |
4dea436d1d4807a363433d7fa7130016a56d3ff00bfe4af7dc94a523994040a7 | Python | 14,309 | 467 | {
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"# Import functions #\n",
"import argparse,datetime,os,sys,time\n",
"\n",
"try:\n",
" import plotly.graph_objects as go\n",
"except:\n",
" go = None \n",
"\n",
... |
c974ea8b718713dfb38a641dfd1f60122c121bebf066311dca8784dfab5cc7e1 | Python | 14,312 | 359 | """
MeasureImageAreaOccupied
========================
**MeasureImageAreaOccupied** measures the total area in an image that
is occupied by objects.
This module reports the sum of the areas and perimeters of the objects
defined by one of the **Identify** modules, or the area of the
foreground in a binary image. If the... |
57d585aae31517f9d0b165cccb1024845ebd04532e0812a8e784a173ffa36ac9 | Python | 14,320 | 449 | # coding=utf-8
# Copyright 2020 The SimCLR Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or... |
3e6c7ea9fd02c01d95700b1e7496fecc34b65664556cabcf6084bc3434422c0b | Python | 14,331 | 405 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Oct 10 14:34:18 2021
@author: goyalp
"""
import torch
import os, time
import Functions.utils as utils
from tqdm.autonotebook import tqdm
import Functions.diff_operators as diff_operators
from Functions.utils import get_batch_data
from torch.optim.lr_sc... |
d54ecdc02a0fa3724e34814c8ca2ed04bc30ce9381a830eb19051121f62d370f | Python | 14,331 | 496 | #!/usr/bin/env python3
import os
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from baycomp import two_on_single
from etspredict.prediction.scoring_utils import compare_propabilites
####################################################################... |
e4a134494f3ade804a1026666798b3a573ac18342f5574803e55dfa205330e39 | Python | 14,365 | 383 | import pandas as pd
import os
import sys
import time
import numpy as np
import torch
import matplotlib.pyplot as plt
import torch.nn.functional as F
from torch_geometric.loader import DataLoader as GraphDataLoader
from sklearn.preprocessing import StandardScaler,MinMaxScaler
from utils import get_time_dif, fix_batch, t... |
7dad7da4375c48abdc1e672bab5cf949ac6f52cda1c742272294ed51b450622a | Python | 14,377 | 458 | import torch.nn as nn
import math
import torch.utils.model_zoo as model_zoo
import torch.nn.functional as F
import torch
__all__ = ['ResNet', 'resnet18', 'resnet34', 'resnet50', 'resnet101',
'resnet152']
model_urls = {
'resnet18': 'https://download.pytorch.org/models/resnet18-5c106cde.pth',
'resnet... |
4646716c9da81992edc5334943c7cb9acb3602f50f5f8d2019eab23a5bdf77a5 | Python | 14,399 | 250 | """This script estimates TRFs for several models and saves them"""
from pathlib import Path
import re
import os
import eelbrain
import mne
import trftools
from utils_TRF import make_source_space
import numpy as np
DATA_ROOT = Path('/project/3027007.02/Scripts_for_publication').expanduser()
language = 'Dutch'
region =... |
09cd97f97034daf1b6cd80c78a03b139c8ac7625f587e3214cc5bad76bfaacd4 | Python | 14,403 | 284 | from hicmatrix import HiCMatrix
import hicmatrix.utilities
import scipy.sparse
from matplotlib import cm
import numpy as np
from . GenomeTrack import GenomeTrack
from .. utilities import change_chrom_names
import logging
import copy
DEFAULT_MATRIX_COLORMAP = 'RdYlBu_r'
logging.basicConfig(level=logging.DEBUG)
log = lo... |
88058dd6c5d3e564796f6502fad19d50c360e5a35875c9519582560bd155a4b1 | Python | 14,404 | 261 | #### Master Script 05f: Compile robustness check results and token incidences to dropout extraneous variables ####
#
# Shubhayu Bhattacharyay
# University of Cambridge
# email address: sb2406@cam.ac.uk
#
### Contents:
# I. Initialisation
# II. Compile and save bootstrapped robustness check dataframes
# III. Calculate c... |
f93a5c3f00451e2ce0ba2250e4aa1898c80c51088e4ca4d596f7dfe8571f543f | Python | 14,406 | 303 | import os
import random
import torch
import yaml
import json
import argparse
import numpy as np
import pandas as pd
from tqdm import tqdm
from pprint import pprint
import torch.nn as nn
import asteroid
from asteroid.utils import tensors_to_device
from data import *
from sklearn.metrics import balanced_accuracy_score,... |
49d083c344e89322423e65a9e043036abf9369e1f39007ec3e6b9e7a0aea7b81 | Python | 14,413 | 348 | from abc import abstractmethod
import matplotlib.pyplot as plt
import numpy as np
from .spiketrain import SpikeTrainsPlotter
from ..spiketrain import SpikeTrain
class FitPlotter:
def __init__(self, ic=None, model=None, optimizer=None, neuron=None, file=None, log_likelihood_normed=None,
z=None,... |
77f540822c8e3df48785d52093367c5577f71149e29d2c5d954451f37b4d382c | Python | 14,414 | 428 | from typing import Annotated, Any, Dict, List, Optional, Tuple, Union
import numpy
import scipy.ndimage
from numpy.typing import NDArray
from pydantic import BaseModel, ConfigDict, Field, validate_call
from cellprofiler_library.functions.measurement import (
compute_center_distances,
compute_per_bin_distribut... |
63e5b29be11d43ab32dd129728098b98022ac26bd2b79e3eb9237de9c8fceef8 | Python | 14,428 | 395 | # Created by: Deserno, M. et. al., 2023 for https://www.nature.com/articles/s41598-023-38213-7
# Experimental code to match detections globally over video frames
import copy
import itertools
import pickle
import cv2
import matplotlib.pyplot as plt
import numpy as np
import pycocotools.mask as mask
import scipy.optimi... |
ec4a78c83ced51dee99f68efeb2495fb5c42808a05d7e9f49188ab38aefe95d3 | Python | 14,431 | 417 | import os
import sys
import glob
import time
import math
import argparse
import numpy as np
# Computer Vision
import cv2
from scipy import ndimage
from skimage.transform import resize
# Visualization
import matplotlib.pyplot as plt
plasma = plt.get_cmap('plasma')
# UI and OpenGL
from PySide2 import QtCore, QtGui, Qt... |
11d32d78812bdcfa9b16301481b5cc1585bbc3d8f6fca89335f4d81b68831b66 | Python | 14,438 | 379 | from genericpath import exists
import torch
import torch.nn as nn
import numpy as np
from tqdm import tqdm
import os
from torch.utils.data import Dataset
from torchvision.io import read_image
import torchvision
import pandas as pd
from sklearn.model_selection import train_test_split
from torchvision import transforms
f... |
6b5e3f9a8140a85c3fd5993e2a0efcda2ed2f2dd78f0a6241268f825fe8fb27c | Python | 14,452 | 371 | import numpy as np
import torch
import os
import glob
# from .runner import Runner
import torch.distributed as dist
from utils.parallel import get_dist_info
from utils.display import display_metrics_dict
from utils.evaluation import AverageMeter, accuracy, fuzziness
class NCRunner:
"""The runner for Checking Neur... |
ffe9aeea5a0b6e249efedec6f9dbb39fbe0ba1c01e38d9f9d33d2dd8ca7d8a6c | Python | 14,505 | 359 | """Layout rules: canonical ordering, offsets, and coordinate space.
Everything here maintains the store's structural invariants. The discipline that
matters, learned the hard way: **offsets are a compiled index over the parent
columns, never a second source of truth** (I2). Permuting the offsets directly
and patching ... |
3e832a3f57d73d2b266a9f4c5f72c22c452ad7ce692deca0f698e27f7db5b5b6 | Python | 14,509 | 290 | import numpy
import skimage.segmentation
from numpy.typing import NDArray
from typing import Tuple, Annotated, Optional, List, Any, Union
from pydantic import Field, validate_call, ConfigDict, BaseModel
from cellprofiler_core.utilities.core.object import crop_labels_and_image
from cellprofiler_library.types import Ima... |
ba11ef387453031e00371bf694a5df067e8183806ba2acdbefba9e9158d77852 | Python | 14,528 | 381 | import typing, sys
import torch
import torch.nn as nn
import torch.nn.functional as F
from GANDLF.models.seg_modules.add_conv_block import add_conv_block
from GANDLF.models.seg_modules.add_downsample_conv_block import (
add_downsample_conv_block,
)
from GANDLF.models.unet import unet
from .modelBase import ModelBa... |
b81fb9b3cb6ba412bdc8c58f781c9f1d07910c0f00d091906b599765c4384e6d | Python | 14,550 | 344 | #!/usr/bin/env python3
# Copyright 2021 Alexander Meulemans, Matilde Tristany, Maria Cervera
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... |
89c6582572ece417cffaf2b4d621853ae0df1973a55622d5c3e23c23c4648172 | Python | 14,556 | 485 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created in 10.2022
@author: Nikolai M Chapochnikov
"""
# timing stuff
# start_time = timeit.default_timer()
# do something
# elapsed = timeit.default_timer() - start_time
# print(elapsed)
# %%
# ####################################################################... |
9d3997df9fe7393945229918b540d656332f136b0b8d77d49868f7fd9ae32b48 | Python | 14,559 | 410 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Util functions for megsim.
"""
from math import modf
import numpy as np
from numpy.testing import assert_array_equal, assert_array_almost_equal
from mne.io.constants import FIFF
from mne.transforms import rotation3d_align_z_axis
import matplotlib.pylab as plt
from mne... |
34fa4b766910edd56cef9c8d9c3250e2aec07c913dcc588f38ea43243957a489 | Python | 14,566 | 445 | """Guided learning mode — LLM-assisted landmark placement on MRI.
Routes
------
GET /learn Render the guided learning page
GET /learn/nifti Serve MNI152NLin2009cAsym T1w NIfTI
(downloads from TemplateFlow and caches locally
on first re... |
5edd06925ea2a52d63e66af511707bcb653f222d35db949931f7c57f708fba9b | Python | 14,573 | 374 | """ Classifier head and layer factory
Hacked together by / Copyright 2020 Ross Wightman
"""
from collections import OrderedDict
from functools import partial
from typing import Optional, Union, Callable
import torch
import torch.nn as nn
from torch.nn import functional as F
from .adaptive_avgmax_pool import SelectAd... |
7e52105a55dc7be3b3265fadff1fd0a288db6076baed480362bad22552f4fabc | Python | 14,584 | 323 | """
Authors: Mingjian He <mh1@stanford.edu>
Proloy Das <pd640@mgh.harvard.edu>
source_loc_utils module implements supporting functions for dynamic source localization
"""
import torch
import mne
import numpy as np
from somata.exact_inference import djkalman_conv_torch
def patch_decompose(fwd, src_patch, di... |
eaaeb141c294e88752c4d380810131bfc621cd7c7c9d8e8aa49d5bb568b0942a | Python | 14,601 | 396 | from __future__ import annotations
import copy
import hashlib
import importlib.util
import json
import shutil
from pathlib import Path
from typing import Any
import pytest
from jsonschema import ValidationError
ROOT = Path(__file__).resolve().parents[3]
SPEC = importlib.util.spec_from_file_location(
"dm_catalog"... |
4a8ddd8eab011bae40a8838ebbbc5e1e60618aa881159da2ce7e4bc71d158517 | Python | 14,612 | 440 | import unittest
import pytest
from cellprofiler_core.setting import ValidationError
from cellprofiler_core.setting.filter import Filter, FilterPredicate
from cellprofiler_core.setting.filter._filter import LITERAL_PREDICATE, OR_PREDICATE
from cellprofiler_core.setting.range import (
IntegerOrUnboundedRange,
F... |
3f4499e933f037cfaada49cbcc6d997b224bc96c6436367f7250ba9314f4e49b | Python | 14,633 | 359 |
import numpy as np
from skimage.transform import resize
from skimage.transform import resize
from scipy.ndimage.interpolation import map_coordinates
from collections import OrderedDict
RESAMPLING_SEPARATE_Z_ANISO_THRESHOLD = 3
def uniform(low, high, size=None):
"""
wrapper for np.random.uniform to allo... |
8bf9173db0fe57b88faa29f124cb3635a6715d38b8bb40968ee8f4c3048b2eba | Python | 14,656 | 416 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any... |
01eb37927a118b9283d63d6d563ae0c751514a2e2c3e5c713192b75a73355374 | Python | 14,667 | 361 | import os, torch, random, pickle, time
from argparse import ArgumentParser
import numpy as np
import datetime
import torch.nn as nn
import torch.nn.functional as F
import torch.backends.cudnn as cudnn
from torch.nn.parallel.scatter_gather import gather
import load_data as ld
import dataset
import transforms
from parall... |
e102e4faf8faa3e9747add8a9262ea4692d137d905ef5a5dec8bc50358bc75a8 | Python | 14,680 | 331 | # -*- coding: utf-8 -*-
"""
molvs.charge
~~~~~~~~~~~~
This module implements tools for manipulating charges on molecules. In particular, :class:`~molvs.charge.Reionizer`,
which competitively reionizes acids such that the strongest acids ionize first, and :class:`~molvs.charge.Uncharger`,
which attempts to neutralize i... |
6352f22214b08552b44f928cd92ddd843790f3f5ae462edf0dfffdc1df554efc | Python | 14,689 | 328 | import bisect
import collections
import torch
from .event_handling import find_event
from .interp import _interp_evaluate, _interp_fit
from .misc import (_compute_error_ratio,
_select_initial_step,
_optimal_step_size)
from .misc import Perturb
from .solvers import AdaptiveStepsizeE... |
a7a7e5d6aada30ecf756e269a2ac01ae2bd8633ad971c4bb0760fc9e71ef5b2a | Python | 14,694 | 298 | import numpy as np
import nengo
from . import PathIntegration, CircularConvolution, Product
# import os
# import sys
# sys.path.append("../")
# from sspspace import HexagonalSSPSpace
class SLAMLoihiNetwork(nengo.network.Network):
r""" Nengo network that performs simultaneous localization and mapping (SLAM), modi... |
44e9d4648fc80585a9d3a5bd1f831a655183f57e4eee7e9c725d1970a553ca3d | Python | 14,736 | 304 | import os
import time
import torch
from torch.utils.data import DataLoader, TensorDataset
from einops import rearrange
from itertools import combinations
from model.egnn import EGNN_Network
from model.molformer import Molformer
from utils.utils import parse_args, set_seed
def main(batch_test=True, min_particle=10, m... |
895b898d520a42f736a01e44d31991bdedd5114a0d31da28b6555074bd6c5c24 | Python | 14,790 | 376 | #!/usr/bin/env python3
import getopt
import os
import multiprocessing
import pysam
import time
import logging
from sys import argv, exit
from pybedtools import BedTool, cleanup, set_tempdir, get_tempdir
def getAnno(LR, RR, genes):
"""
:param LR: BedTool object with only one position defined for the Left Bre... |
b1b47c739fdb739be279b87ba694dbc69acc11146dca2910e599a0f6bf25b5c9 | Python | 14,801 | 464 | """
Convert NBDC data dictionary to ReproSchema format.
This module handles conversion of NBDC (Neurodata Without Borders/Data Coordinating Center)
study data from various formats (Parquet, CSV, RDS) to ReproSchema JSON-LD.
"""
import logging
from pathlib import Path
from typing import Any, Dict, Optional, Tuple
imp... |
b07274005010c579581ae4a70388467957cb9f14e7565cb84931b63c145d84a5 | Python | 14,816 | 404 | import collections.abc
import math
import re
from collections import defaultdict
from copy import deepcopy
from itertools import chain
from typing import Any, Callable, Dict, Iterator, List, Optional, Tuple, Type, Union
import torch
import torch.utils.checkpoint
from torch import nn as nn
from torch import Tensor
fro... |
2c111f27d9a242e970d4eee6a15c871f55bf41f69221d9f6a8c2c6bcfff4f40d | Python | 14,838 | 481 | from __future__ import absolute_import
import math
import copy
import numpy
import scipy.ndimage
from . import lapjv
invalid_match = 1000000 # limiting the choices of the algorithms
def euclidean_dist(point1, point2):
"""Compute the Euclidean distance between two points.
Parameters
----------
point... |
7ff18e46a86b457a4db2c67d5b708ab468e5268da66cb5e45f6dc3bd968fed92 | Python | 14,844 | 383 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any... |
159097093abf41a2b9aaaac836305110691c4afaf44cd143604187ad142b19a5 | Python | 14,880 | 365 | #!/usr/bin/env python3
# Copyright 2021 Alexander Meulemans, Matilde Tristany, Maria Cervera
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... |
ed8ca6368e105ccf4d9b45f81b8ccc312dc0b9f0016c0cfa604b606433ae1f54 | Python | 14,922 | 452 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any... |
e39eb68fb56abbb4f995fcca091bafce5fd1283321fe650ba14a67d87c1dab45 | Python | 14,923 | 350 | """Preserve Godlewski et al.'s complete supplementary metabolomics table as CSV."""
from __future__ import annotations
import argparse
import csv
import gzip
import hashlib
import json
import platform
import shutil
import sys
import zlib
from collections import Counter
from datetime import UTC, datetime
from pathlib ... |
1c18e626ba627a768463518bded5ef549279378d7c579cf77d6be2c9d9144960 | Python | 14,924 | 442 | import itertools
import matplotlib.pyplot as plt
import numpy as np
from .masks import extend_trues, shift_mask
from .signals import mask_extrema, threshold_crossings
from .spiketrain import SpikeTrain
from .utils.abf import load_data, load_protocol
from .utils.time import get_arg, get_dt, searchsorted
class IClamp:... |
aa9069288403259c1235b280a3597dbf6e8864b940479024f241b740195d69ec | Python | 14,958 | 291 | """
ClinicalASL - Clinical Arterial Spin Labeling processing pipeline
Main pipeline script for processing ASL MRI data.
Repository: https://github.com/JSIERO/ClinicalASL
Author: Jeroen Siero
Institution: UMCU (University Medical Center Utrecht), The Netherlands
Contact: j.c.w.siero@umcutrecht.nl
Description:
Thi... |
624c4d20c825a5c175c3048985a3bb78e94d35577c2eefa8fe168ed1122527e0 | Python | 14,964 | 367 | """
AFIDS Template Analysis Script
Analyzes all human and macaca FCSV template files to compute inter-template variability.
"""
import os
import json
import csv
import math
from pathlib import Path
from collections import defaultdict
# ─── LANDMARK METADATA ────────────────────────────────────────────────────────
# ... |
481edb732fdbf41f936443efd2ee4280ee65687c8392acc524a0e67487f63010 | Python | 14,973 | 437 | import numpy as np
import math
import scipy
def sparsity_to_x_intercept(d, p):
sign = 1
if p > 0.5:
p = 1.0 - p
sign = -1
return sign * np.sqrt(1-scipy.special.betaincinv((d-1)/2.0, 0.5, 2*p))
def get_mean_and_ci(raw_data, n=3000, p=0.95):
"""
Gets the mean and 95% confidence int... |
fe1b02f72f5faca244c00f3660d8244386442303d2125484ac1f64130801992f | Python | 15,005 | 377 | import datetime
import logging
import math
import os
import numpy as np
import pandas as pd
from keras import backend as K
from keras.callbacks import ModelCheckpoint, ReduceLROnPlateau, LearningRateScheduler
from sklearn import metrics
from sklearn.base import BaseEstimator
from sklearn.metrics import accuracy_score
... |
6fa2160579bf816f33ab201e04d6d04380e674cb92303bfabfb3f25a626d568f | Python | 15,010 | 470 | #!/usr/bin/env python3
# Copyright 2021 Alexander Meulemans, Matilde Tristany, Maria Cervera
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... |
22a229dd095958a2d54ab445160e453a63ae01166971282df3878d3aead219c3 | Python | 15,018 | 393 | from torch.nn.modules.batchnorm import BatchNorm2d
from torchvision.ops.misc import FrozenBatchNorm2d
import timm
import torch
import pytest
from timm.utils.model import freeze, unfreeze
from timm.utils.model import ActivationStatsHook
from timm.utils.model import extract_spp_stats
from timm.utils.model import _freez... |
0a30a7a6a8ca944c0ef00529599e7bc47da81aa9491b403c7189681438477ed5 | Python | 15,024 | 382 | # This file is part of pyunicorn.
# Copyright (C) 2008--2026 Jonathan F. Donges and pyunicorn authors
# URL: <https://www.pik-potsdam.de/members/donges/software-2/software>
# License: BSD (3-clause)
#
# Please acknowledge and cite the use of this software and its authors
# when results are used in publications or publi... |
d8ab0e0fad163ffe9020aeec578952c69e50d83e21c27af0608a763712206ada | Python | 15,048 | 440 | """
Module that implements functionality regarding segmentations
- open segmentations from input file path
- relabel segmentations (adapting data type if requested)
- compute segmentation statistics such as
- number of segments
- segment size
- segment slices
- compute segmentation ARI error
- compute segmentat... |
c00df66340778d00fb2ed19a3a1e5b11149264c438ddec9f1ecc1a33bfa3e7ae | Python | 15,051 | 448 | """Graphical visualisation support for provONE.model.
This module produces graphical visualisation for ProvONE graphs.
Requires pydot module and Graphviz.
References:
* pydot homepage: https://github.com/erocarrera/pydot
* Graphviz: http://www.graphviz.org/
* DOT Language: http://www.graphviz.org/doc/info/la... |
9a9fa761c334fe5e53da5e90ef0661269e131af5d4e16b4c97f35a7286d8d5f6 | Python | 15,068 | 402 | import inspect
from datetime import datetime
import neuron
import numpy as np
from .globalFunctions.utils import Dict, replaceDictODict
class simParams(object):
def __init__(self, simParamsDict=None):
# Flags
self.test_flag = False
self.plot_flag = True
self.save_flag = True
... |
290dc65e132f0f3dd8d485a471541045fb5e194c1db8185204a83f944c21d74b | Python | 15,073 | 339 | import torch
import torchvision
import torch.nn.functional as f
import math
from tqdm import tqdm
from utils import radam
import utils.viz_utils as viz_utils
from models.style_networks import SemSegE2VID
import training.base_trainer
from evaluation.metrics import MetricsSemseg
from utils.loss_functions import TaskLo... |
3a4658abbbb3ca206f08a1dec2cfab5ab622f8ccd6eb0fab39c5dcc4351360a7 | Python | 15,103 | 450 | import nibabel as nib
import numpy as np
from dipy.segment.mask import crop, bounding_box
from fury import actor, window
from fury.window import Scene
from traitlets import Unicode, Float, Integer, Dict, Bool, List, Enum
from mrHARDI.base.application import (mrHARDIBaseApplication,
... |
95ba0ee5dff4d2e8446992981251638a804bb28a106c8e285e433f505fde8e97 | Python | 15,108 | 397 | import os
import logging
import numpy as np
import random
import functools
import torch
import torch.nn.functional as F
from torch import nn
from torch_geometric.nn import MessagePassing
from torch_scatter import scatter_add
def tuple_sum(*args):
"""
Sums any number of tuples (s, V) elementwise.
"""
r... |
ef23ea468c7a7b9301f95cc7c6603892df96e5d5b0125c439b59a6d35f6337be | Python | 15,155 | 366 | import os, shutil, yaml, docker, tarfile, io, sysconfig
from typing import Optional
# import copy
deploy_targets = [
"docker",
#'singularity',
#'onefile'
]
mlcube_types = ["model", "metrics"]
def run_deployment(
mlcubedir: str,
outputdir: str,
target: str,
mlcube_type: str,
entrypoi... |
d19ba9d7de2e3c20d739dbb7291655f3e337585012564b679ddefc2f89a92b44 | Python | 15,175 | 414 | from typing import Literal
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from scipy import integrate
from scipy.ndimage import binary_dilation, binary_erosion
def selection_generator(df: pd.DataFrame, unique_values_columns: dict, verbose: bool = False, **kwargs) -> np.ndarray:
idx = np.o... |
fd6f32378a1776a10ff8676b69e30dce6eb30df1609df185430438509388bcb5 | Python | 15,178 | 339 | """
Author: "Keitaro Yamashita, Garib N. Murshudov"
MRC Laboratory of Molecular Biology
This software is released under the
Mozilla Public License, version 2.0; see LICENSE.
"""
from __future__ import absolute_import, division, print_function, generators
import argparse
import gemmi
import numpy
import time
import... |
3e8c52fee2fd9daa72d6653e94ddafcbada4ffd7770195c82e1329fa29797e95 | Python | 15,198 | 487 | # -*- coding: utf-8 -*-
"""
pysteps.datasets
================
Utilities to download the pysteps data and to create a default pysteps configuration
file pointing to that data.
.. autosummary::
:toctree: ../generated/
download_pysteps_data
create_default_pystepsrc
info
load_dataset
"""
import gzip... |
314a9b8ade829c2f9b6b3effe9d124efb86048c8d92b15955830bd1826e1d6a3 | Python | 15,210 | 484 | """
@author: Nikolai M Chapochnikov
"""
import numpy as np
from scipy import linalg as LA
from functions.nmf import get_init_matrix
from functions.general import rectify, FLOAT_TYPE, EPSILON
from typing import Tuple
def mat_mul(A, B, alpha=1):
"""
https://www.benjaminjohnston.com.au/matmul
"""
retur... |
520354d227a3b1278444bd39a6e3991c78ca30f32a69aaadbd3f84aaebaff219 | Python | 15,213 | 481 | # This file is part of pyunicorn.
# Copyright (C) 2008--2026 Jonathan F. Donges and pyunicorn authors
# URL: <https://www.pik-potsdam.de/members/donges/software-2/software>
# License: BSD (3-clause)
#
# Please acknowledge and cite the use of this software and its authors
# when results are used in publications or publi... |
be4266faf0cd1bee9b6377593d066afadec15c7b2d8a6c9196434566f5d25e77 | Python | 15,213 | 399 | #################################
#
# Imports from useful Python libraries
#
#################################
import numpy
import scipy.ndimage
#################################
#
# Imports from CellProfiler
#
##################################
# Reference
#
# If you're using a technique or method that's used in t... |
1b6065d94f260082cea28f67a5bf9169a417aa483defd641ac9fb7d2956eef7e | Python | 15,214 | 434 | from __future__ import annotations
import bz2
import gzip
import json
from collections.abc import Callable
from pathlib import Path
import numpy as np
import pandas as pd
import pytest
from conftest import (
CORPUS,
EXPECTED_DIGEST,
FIXTURE,
LIBSVM_DIGEST,
LIBSVM_FIXTURE,
LIBSVM_OPTIONS,
O... |
586e9fbe912745f92b4400f177afd62bb449b4eb8eb1875a0b98b1eb55fabaca | Python | 15,245 | 359 | import numpy as np
import time
import nengo
import sys, os
sys.path.insert(1, os.path.dirname(os.getcwd()))
#os.chdir("..")
import sspslam
import argparse
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation, PillowWriter
from matplotlib.gridspec import GridSpec
from matplotlib.colors import ... |
61dea925d126d050812c0810284a364fa2c4bb4ef97e6e21ad3f7d613f999ee9 | Python | 15,247 | 343 | """Small optimizer helpers shared by timm optimizer implementations."""
import functools
import os
from typing import Any, Callable, Dict, List, Optional, Sequence, Union
import torch
from torch import Tensor
try:
from torch.optim.optimizer import _default_to_fused_or_foreach
except ImportError:
_default_to_f... |
ef0072f33f18cfe43ca142917fb6d494d1d37e8b1589c263bcc4f925a3799774 | Python | 15,249 | 422 | #!/usr/bin/env python
__author__ = "Marc Steffen Seibel and Thomas Jochmann"
import os
os.environ['MNE_USE_NUMBA']='False'
import pandas as pd
import numpy as np
import mne
from collections import OrderedDict
import settings
import tensorflow as tf
from tensorflow.keras import backend as K
import time
imp... |
7ceac3644b134dd81fa0b3542cd526b20f35a032df3bba9b4f5dc966b174f524 | Python | 15,262 | 430 | from typing import Any, Dict, List
import numpy as np
import pytest
from hypothesis import given, settings, strategies
from scipy import sparse
import xgboost as xgb
from xgboost.testing import (
IteratorForTest,
make_batches,
make_batches_sparse,
make_categorical,
make_sparse_regression,
)
from x... |
87cfc9ad781c4c95b8d48bbd923b0de1aa24a5d2ddf69689663d5c9dbad584ad | Python | 15,278 | 384 | # Implementation of batch-normalized LSTM.
# Some code is from Pytorch source code and https://github.com/jiesutd/LatticeLSTM
import torch
from torch import nn
import torch.autograd as autograd
from torch.autograd import Variable
from torch.nn import functional, init
import numpy as np
# LSTM Cell for words
class Word... |
416a914b9a358ae4b685d1a7119d14d777f31c70253f88e01b85d7ede993d720 | Python | 15,324 | 315 | """
Implementation of a working memory model.
Literature:
Compte, A., Brunel, N., Goldman-Rakic, P. S., & Wang, X. J. (2000). Synaptic mechanisms and
network dynamics underlying spatial working memory in a cortical network model.
Cerebral Cortex, 10(9), 910-923.
Some parts of this implementation are inspired by materi... |
bf98f709b03dab4e61a6c59aef92229d6d5844e9db6dc5fee612f71fd9c193f2 | Python | 15,333 | 482 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Mar 26 11:56:59 2019
@author: Nikolai M Chapochnikov
"""
# %%
# ################################# IMPORTS ###################################
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
# for colors and gradients
# im... |
ef2846cf1333b55c6a8c721e23f94d932d422fbebfe2248c75717a051bd814a1 | Python | 15,365 | 368 | from .forward_pass import validate_network
from .generic import create_pytorch_objects
import os, sys
from typing import Optional
from pathlib import Path
import pandas as pd
# hides torchio citation request, see https://github.com/fepegar/torchio/issues/235
os.environ["TORCHIO_HIDE_CITATION_PROMPT"] = "1"
import tor... |
f7e633e26d0df2eb8a9dd02c12ac9431301e95e74e10653cbd29e0b699e85fab | Python | 15,383 | 331 | """Scheduled batch sampling and transform dispatch for map-style datasets."""
import math
from itertools import islice
from typing import Any, Callable, Iterator, List, Optional, Sequence, Tuple, Union
import torch
from torch.utils.data import Dataset, Sampler
class ScheduledBatchSampler(Sampler[List[Tuple[Any, int... |
adb7be1f58027b957d2cf682226338616220d99b0cd7293f0a517ea642d31611 | Python | 15,401 | 341 | #!/usr/bin/env python3
# Copyright 2021 Maria Cervera
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law o... |
f5174611197b9a12bbc842e71137a01c9701e991fade8e1112f1878e6a13dec9 | Python | 15,413 | 419 | import sys
import numpy
import six.moves
import cellprofiler_core.image
import cellprofiler.modules.measuregranularity
import cellprofiler_core.object
import cellprofiler_core.pipeline
import cellprofiler_core.workspace
import tests.frontend.modules
print((sys.path))
IMAGE_NAME = "myimage"
OBJECTS_NAME = "myobjec... |
82f6696c6dd25c61d82b4512f1c39a6a656fbafba5a60bb07b32d1a64e1f9124 | Python | 15,452 | 432 | """
pysteps.nowcasts.sprog
======================
Implementation of the S-PROG method described in :cite:`Seed2003`
.. autosummary::
:toctree: ../generated/
forecast
"""
import time
import numpy as np
from pysteps import cascade, extrapolation, utils
from pysteps.nowcasts import utils as nowcast_utils
fro... |
2ad187cdafec12359fba82f71e05baa460083bd48e6832e09f0d9046d73887f5 | Python | 15,516 | 435 | # important note:- Do not change any print stings if you intended to use pyOS5 GUI
#@ Author : Sampath
#This script is to run DMTP (Delayed Matched Response) working memory task and for more deatils look at Task_desription.ppt
#SP => Sample Phase
#CP => Choice Phase
import random as rnd
import hardware_definition as ... |
075748ffae6c2e400345d59fdf5c5a9795e1e3a8a1dbb5d5398fdc73b73b3d53 | Python | 15,546 | 299 | #### Master Script 06a: Prepare for sensitivity analysis to account for differences in patient stay ####
#
# Shubhayu Bhattacharyay
# University of Cambridge
# email address: sb2406@cam.ac.uk
#
### Contents:
# I. Initialisation
# II. Construct a list of predictions to recalculate after removing dynamic variable tokens
... |
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